Trustworthy AI in Julia
The Alan Turing Institute
Delft University of Technology
2024-05-08
Introduction
Economist by training, previously Bank of England, currently 3rd year PhD in Trustworthy AI @ TU Delft.
Motivation
Why Trustworthy AI and why in Julia?
- Opaque AI technologies have entered the public domain with far-reaching stakes.
- These technologies are here to stay, so at best, we can make them more trustworthy.
- Julia has an edge:
- Transparency: most packages are written in pure Julia.
- Intuitiveness: great Lisp-like support for symbolic computing.
- Community: welcoming, supportive and diverse (sort of!).
- Autodiff: top-notch support, which helps with common XAI approaches.
Outline
- Taija: A brief overview of the Taija ecosystem.
- Deep Dive: A closer look at some of our core packages.
- The Journey: “I’ll try out Julia for this PhD”—3 years later.
Taija
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“Algorithms do not listen, nor do they bend”
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“We’re fascinated with robots because they are reflections of ourselves.”
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Questions?
With thanks to my co-authors Andrew M. Demetriou, Antony Bartlett, and Cynthia C. S. Liem and to the audience for their attention.
Quote sources
- “There! It’s sentient”—that engineer at Google (probably!)
- “Algorithms don’t listen, nor do they bend”—Cathy O’Neil
- “We’re fascinated with robots because they are reflections of ourselves.”—Ken Goldberg